Import and process data

Learning

Model: Correct responses by continuous age, trial, block number, and block condition

  correct_response_made
Predictors Odds Ratios SE
age scaled 1.1540 0.0918
learning trial scaled 1.2940 0.0420
reward condition1 1.6592 0.1106
block number scaled 1.1736 0.0605
age scaled × learning
trial scaled
1.0075 0.0325
age scaled × reward
condition1
1.0787 0.0717
learning trial scaled ×
reward condition1
1.1362 0.0351
age scaled × block number
scaled
1.0387 0.0534
learning trial scaled ×
block number scaled
1.0197 0.0229
reward condition1 × block
number scaled
1.1224 0.0603
age scaled × learning
trial scaled × reward
condition1
0.9718 0.0298
(age scaled × learning
trial scaled) × block
number scaled
0.9782 0.0218
(age scaled × reward
condition1) × block
number scaled
1.0203 0.0547
(learning trial scaled ×
reward condition1) ×
block number scaled
1.0134 0.0254
(age scaled × learning
trial scaled × reward
condition1) × block
number scaled
0.9767 0.0243
Random Effects
σ2 3.29
τ00 subject_id 0.20
τ11 subject_id.re1.learning_trial_scaled 0.02
τ11 subject_id.re1.reward_condition1 0.14
τ11 subject_id.re1.block_number_scaled 0.08
τ11 subject_id.re1.learning_trial_scaled_by_reward_condition1 0.02
τ11 subject_id.re1.learning_trial_scaled_by_block_number_scaled 0.01
τ11 subject_id.re1.reward_condition1_by_block_number_scaled 0.09
τ11 subject_id.re1.learning_trial_scaled_by_reward_condition1_by_block_number_scaled 0.01
ρ01  
ρ01  
ICC 0.06
N subject_id 34
Observations 14688
Marginal R2 / Conditional R2 0.105 / 0.157

Model: Correct response to first appearance of each stimulus

  correct_response_made
Predictors Odds Ratios SE
age scaled 1.0283 0.0597
category rep scaled 1.1410 0.0590
reward condition1 1.3145 0.0910
block number scaled 0.9974 0.0501
age scaled × category rep
scaled
0.9612 0.0512
age scaled × reward
condition1
1.0676 0.0740
category rep scaled ×
reward condition1
1.1810 0.0610
age scaled × block number
scaled
1.0176 0.0514
category rep scaled ×
block number scaled
0.9513 0.0472
reward condition1 × block
number scaled
1.0972 0.0551
age scaled × category rep
scaled × reward
condition1
1.0467 0.0557
(age scaled × category
rep scaled) × block
number scaled
1.1090 0.0583
(age scaled × reward
condition1) × block
number scaled
1.0949 0.0553
(category rep scaled ×
reward condition1) ×
block number scaled
1.0052 0.0499
(age scaled × category
rep scaled × reward
condition1) × block
number scaled
0.9223 0.0484
Random Effects
σ2 3.29
τ00 subject_id 0.03
τ11 subject_id.re1.reward_condition1 0.08
ρ01  
ρ01  
ICC 0.01
N subject_id 34
Observations 1836
Marginal R2 / Conditional R2 0.047 / 0.055

Model: Category win-stay lose-shift

  WSLS
Predictors Odds Ratios SE
age scaled 1.0183 0.0373
learning trial scaled 1.0058 0.0181
reward condition1 1.3492 0.0469
block number scaled 1.0778 0.0194
age scaled × learning
trial scaled
0.9382 0.0168
age scaled × reward
condition1
1.0573 0.0366
learning trial scaled ×
reward condition1
1.1178 0.0202
age scaled × block number
scaled
0.9941 0.0178
learning trial scaled ×
block number scaled
0.9921 0.0179
reward condition1 × block
number scaled
1.0728 0.0193
age scaled × learning
trial scaled × reward
condition1
0.9967 0.0179
(age scaled × learning
trial scaled) × block
number scaled
0.9848 0.0177
(age scaled × reward
condition1) × block
number scaled
1.0471 0.0187
(learning trial scaled ×
reward condition1) ×
block number scaled
1.0160 0.0183
(age scaled × learning
trial scaled × reward
condition1) × block
number scaled
0.9898 0.0178
Random Effects
σ2 3.29
τ00 subject_id 0.03
τ11 subject_id.re1.reward_condition1 0.03
ρ01  
ρ01  
ICC 0.01
N subject_id 34
Observations 13814
Marginal R2 / Conditional R2 0.036 / 0.046

Memory

Model: AUCs by age, reward condition, memory specificity

  AUC
Predictors Estimates SE
age scaled 0.0058 0.0158
reward condition1 -0.0185 0.0065
foil type1 0.0464 0.0065
age scaled × reward
condition1
0.0063 0.0065
age scaled × foil type1 -0.0063 0.0065
reward condition1 × foil
type1
0.0109 0.0065
age scaled × reward
condition1 × foil type1
-0.0022 0.0065
Random Effects
σ2 0.01
τ00 subject_id 0.01
ICC 0.55
N subject_id 34
Observations 136
Marginal R2 / Conditional R2 0.178 / 0.631

RL modeling

Choice weights

Model: Choice weights by block condition and age

  est
Predictors Estimates SE
abstraction1 0.0563 0.0800
reward condition1 0.0574 0.0800
age scaled 0.3045 0.1415
abstraction1 × reward
condition1
0.1009 0.0800
abstraction1 × age scaled -0.0777 0.0803
reward condition1 × age
scaled
0.0153 0.0803
(abstraction1 × reward
condition1) × age scaled
-0.0266 0.0803
Random Effects
σ2 0.87
τ00 subject_id 0.46
ICC 0.34
N subject_id 34
Observations 136
Marginal R2 / Conditional R2 0.081 / 0.398

Model: Exemplar choice weights by condition

  est
Predictors Estimates SE
reward condition1 -0.0435 0.0814
Random Effects
σ2 0.45
τ00 subject_id 1.00
ICC 0.69
N subject_id 34
Observations 68
Marginal R2 / Conditional R2 0.001 / 0.689

Relations between choice weights and points earned

## Mixed Model Anova Table (Type 3 tests, S-method)
## 
## Model: total_points ~ age_scaled * beta_scaled * abstraction * reward_condition + 
## Model:     (1 | subject_id)
## Data: beta_ests_points
##                                                 Effect        df          F
## 1                                           age_scaled  1, 31.94       2.00
## 2                                          beta_scaled 1, 119.78    7.97 **
## 3                                          abstraction  1, 89.40       0.43
## 4                                     reward_condition  1, 88.01 165.86 ***
## 5                               age_scaled:beta_scaled 1, 120.00       0.06
## 6                               age_scaled:abstraction  1, 90.31       0.10
## 7                              beta_scaled:abstraction 1, 106.86       0.01
## 8                          age_scaled:reward_condition  1, 88.71       0.51
## 9                         beta_scaled:reward_condition  1, 94.50    9.92 **
## 10                        abstraction:reward_condition  1, 87.91       0.45
## 11                  age_scaled:beta_scaled:abstraction 1, 108.85       0.00
## 12             age_scaled:beta_scaled:reward_condition  1, 94.47       0.07
## 13             age_scaled:abstraction:reward_condition  1, 89.19       0.21
## 14            beta_scaled:abstraction:reward_condition  1, 94.05   10.91 **
## 15 age_scaled:beta_scaled:abstraction:reward_condition  1, 91.51       0.56
##    p.value
## 1     .167
## 2     .006
## 3     .513
## 4    <.001
## 5     .809
## 6     .757
## 7     .942
## 8     .476
## 9     .002
## 10    .502
## 11   >.999
## 12    .796
## 13    .649
## 14    .001
## 15    .458
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

Relations between learning and memory

Do points earned during learning relate to memory?

Model: AUC by points earned, reward condition, age

  AUC
Predictors Estimates SE
age scaled 0.0054 0.0177
points scaled 0.0356 0.0153
abstraction1 0.0404 0.0099
reward condition1 -0.0381 0.0121
age scaled × points
scaled
-0.0123 0.0144
age scaled × abstraction1 -0.0117 0.0093
points scaled ×
abstraction1
-0.0059 0.0113
age scaled × reward
condition1
0.0076 0.0112
points scaled × reward
condition1
0.0052 0.0145
abstraction1 × reward
condition1
0.0141 0.0099
age scaled × points
scaled × abstraction1
-0.0103 0.0103
age scaled × points
scaled × reward
condition1
-0.0142 0.0128
age scaled × abstraction1
× reward condition1
0.0029 0.0093
points scaled ×
abstraction1 × reward
condition1
0.0111 0.0113
age scaled × points
scaled × abstraction1 ×
reward condition1
0.0079 0.0103
Random Effects
σ2 0.01
τ00 subject_id 0.01
ICC 0.55
N subject_id 34
Observations 136
Marginal R2 / Conditional R2 0.235 / 0.659

Do choice weights relate to memory?

Model: AUC by age, exemplar choice weights, specificity, block condition

  AUC
Predictors Estimates CI
age scaled -0.0019 -0.0343 – 0.0306
beta scaled 0.0171 -0.0075 – 0.0417
abstraction1 0.0509 0.0375 – 0.0642
reward condition1 -0.0163 -0.0297 – -0.0029
age scaled × beta scaled -0.0103 -0.0334 – 0.0128
age scaled × abstraction1 -0.0108 -0.0246 – 0.0030
beta scaled ×
abstraction1
0.0057 -0.0081 – 0.0194
age scaled × reward
condition1
0.0022 -0.0123 – 0.0168
beta scaled × reward
condition1
0.0037 -0.0113 – 0.0187
abstraction1 × reward
condition1
0.0129 -0.0004 – 0.0262
age scaled × beta scaled
× abstraction1
-0.0131 -0.0248 – -0.0013
age scaled × beta scaled
× reward condition1
-0.0038 -0.0161 – 0.0086
age scaled × abstraction1
× reward condition1
-0.0067 -0.0205 – 0.0072
beta scaled ×
abstraction1 × reward
condition1
0.0044 -0.0094 – 0.0181
age scaled × beta scaled
× abstraction1 × reward
condition1
-0.0042 -0.0160 – 0.0075
Random Effects
σ2 0.01
τ00 subject_id 0.01
ICC 0.55
N subject_id 34
Observations 136
Marginal R2 / Conditional R2 0.214 / 0.649

AUC by exemplar choice weights: model effects

Model: AUC by age, category choice weights, specificity, block condition

  AUC
Predictors Estimates SE
age scaled 0.0034 0.0157
beta scaled 0.0161 0.0106
abstraction1 0.0464 0.0064
reward condition1 -0.0185 0.0066
age scaled × beta scaled -0.0133 0.0105
age scaled × abstraction1 -0.0071 0.0065
beta scaled ×
abstraction1
0.0111 0.0065
age scaled × reward
condition1
0.0048 0.0066
beta scaled × reward
condition1
0.0136 0.0073
abstraction1 × reward
condition1
0.0115 0.0064
age scaled × beta scaled
× abstraction1
-0.0008 0.0061
age scaled × beta scaled
× reward condition1
-0.0117 0.0068
age scaled × abstraction1
× reward condition1
-0.0028 0.0065
beta scaled ×
abstraction1 × reward
condition1
0.0003 0.0065
age scaled × beta scaled
× abstraction1 × reward
condition1
-0.0111 0.0061
Random Effects
σ2 0.01
τ00 subject_id 0.01
ICC 0.56
N subject_id 34
Observations 136
Marginal R2 / Conditional R2 0.237 / 0.664

Figure 5F: AUC by category choice weights: model effects